Risk of type 2 diabetes after diagnosed gestational diabetes is enhanced by exposure to PM2.5

Disease types and pathogenic mechanisms induced by PM2.5 in five human systems: An analysis using omics and human disease databases

Atmospheric fine particulate matter (PM2.5) can harm various systems in the human body. Due to limitations in the current understanding of epidemiology and toxicology, the disease types and pathogenic mechanisms induced by PM2.5 in various human systems remain unclear. In this study, the disease types induced by PM2.5 in the respiratory, circulatory, endocrine, and female and male urogenital systems have been investigated and the pathogenic mechanisms identified at molecular level. The results reveal that PM2.5 is highly likely to induce pulmonary emphysema, reperfusion injury, malignant thyroid neoplasm, ovarian endometriosis, and nephritis in each of the above systems respectively. The most important co-existing gene, cellular component, biological process, molecular function, and pathway in the five systems targeted by PM2.5 are Fos proto-oncogene (FOS), extracellular matrix, urogenital system development, extracellular matrix structural constituent conferring tensile strength, and ferroptosis respectively. Differentially expressed genes that are significantly and uniquely targeted by PM2.5 in each system are BTG2 (respiratory), BIRC5 (circulatory), NFE2L2 (endocrine), TBK1 (female urogenital) and STAT1 (male urogenital). Important disease-related cellular components, biological processes, and molecular functions are specifically induced by PM2.5. For example, response to wounding, blood vessel morphogenesis, body morphogenesis, negative regulation of response to endoplasmic reticulum stress, and response to type I interferon are the top uniquely existing biological processes in each system respectively. PM2.5 mainly acts on key disease-related pathways such as the PD-L1 expression and PD-1 checkpoint pathway in cancer (respiratory), cell cycle (circulatory), apoptosis (endocrine), antigen processing and presentation (female urogenital), and neuroactive ligand-receptor interaction (male urogenital). This study provides a novel analysis strategy for elucidating PM2.5-related disease types and is an important supplement to epidemiological investigation. It clarifies the risks of PM2.5 exposure, elucidates the pathogenic mechanisms, and provides scientific support for promoting the precise prevention and treatment of PM2.5-related diseases.

Variations in the LINGO2 and GLIS3 Genes and Gene-Environment Interactions Increase Gestational Diabetes Mellitus Risk in Chinese Women

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.

Gestational and Postpartum Exposure to PM2.5 Components and Glucose Metabolism in Chinese Women: A Prospective Cohort Study

Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6-8 weeks postpartum. Residential PM2.5 and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5 exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5 exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction = 0.003). In the quantile-based g-computation model, NO3- consistently contributed to the combined effect of PM2.5 components on gestational and postpartum FPG. This study was the first to suggest that PM2.5 components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5 components are essential to improving maternal glucose metabolism.

Air pollution exposure and cardiometabolic risk

The Global Burden of Disease assessment estimates that 20% of global type 2 diabetes cases are related to chronic exposure to particulate matter (PM) with a diameter of 2·5 μm or less (PM2·5). With 99% of the global population residing in areas where air pollution levels are above current WHO air quality guidelines, and increasing concern in regard to the common drivers of air pollution and climate change, there is a compelling need to understand the connection between air pollution and cardiometabolic disease, and pathways to address this preventable risk factor. This Review provides an up to date summary of the epidemiological evidence and mechanistic underpinnings linking air pollution with cardiometabolic risk. We also outline approaches to improve awareness, and discuss personal-level, community, governmental, and policy interventions to help mitigate the growing global public health risk of air pollution exposure.

Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas

BACKGROUND

Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas.

METHOD

Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location.

RESULTS

In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %).

CONCLUSION

Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.